In [1]:
ukraineMapsLink="https://github.com/Joaquin-TC/geodfprepro/raw/main/maps%20and%20data/UcraniaMapa.gpkg"

from  fiona import listlayers


#layers in maps
listlayers(ukraineMapsLink)
Out[1]:
['ucrania', 'regiones', 'ciudades', 'capitales', 'hidrografia']
In [2]:
# leeremos la data:

import os
os.environ['USE_PYGEOS'] = '0'

import geopandas as gpd

ucrania=gpd.read_file(ukraineMapsLink,layer='ucrania')
regiones=gpd.read_file(ukraineMapsLink,layer='regiones')
ciudades=gpd.read_file(ukraineMapsLink,layer='ciudades')
capitales=gpd.read_file(ukraineMapsLink,layer='capitales')
hidrografia=gpd.read_file(ukraineMapsLink,layer='hidrografia')
In [3]:
import pandas as pd 
infoseaports=pd.read_csv(os.path.join("data","UpdatedPub150.csv"))

#vemos que hay muchas columnas, nos quedaremos con algunas solamente
infoseaports.columns.to_list()
Out[3]:
['World Port Index Number',
 'Region Name',
 'Main Port Name',
 'Alternate Port Name',
 'UN/LOCODE',
 'Country Code',
 'World Water Body',
 'IHO S-130 Sea Area',
 'Sailing Direction or Publication',
 'Publication Link',
 'Standard Nautical Chart',
 'IHO S-57 Electronic Navigational Chart',
 'IHO S-101 Electronic Navigational Chart',
 'Digital Nautical Chart',
 'Tidal Range (m)',
 'Entrance Width (m)',
 'Channel Depth (m)',
 'Anchorage Depth (m)',
 'Cargo Pier Depth (m)',
 'Oil Terminal Depth (m)',
 'Liquified Natural Gas Terminal Depth (m)',
 'Maximum Vessel Length (m)',
 'Maximum Vessel Beam (m)',
 'Maximum Vessel Draft (m)',
 'Offshore Maximum Vessel Length (m)',
 'Offshore Maximum Vessel Beam (m)',
 'Offshore Maximum Vessel Draft (m)',
 'Harbor Size',
 'Harbor Type',
 'Harbor Use',
 'Shelter Afforded',
 'Entrance Restriction - Tide',
 'Entrance Restriction - Heavy Swell',
 'Entrance Restriction - Ice',
 'Entrance Restriction - Other',
 'Overhead Limits',
 'Underkeel Clearance Management System',
 'Good Holding Ground',
 'Turning Area',
 'Port Security',
 'Estimated Time of Arrival Message',
 'Quarantine - Pratique',
 'Quarantine - Sanitation',
 'Quarantine - Other',
 'Traffic Separation Scheme',
 'Vessel Traffic Service',
 'First Port of Entry',
 'US Representative',
 'Pilotage - Compulsory',
 'Pilotage - Available',
 'Pilotage - Local Assistance',
 'Pilotage - Advisable',
 'Tugs - Salvage',
 'Tugs - Assistance',
 'Communications - Telephone',
 'Communications - Telefax',
 'Communications - Radio',
 'Communications - Radiotelephone',
 'Communications - Airport',
 'Communications - Rail',
 'Search and Rescue',
 'NAVAREA',
 'Facilities - Wharves',
 'Facilities - Anchorage',
 'Facilities - Dangerous Cargo Anchorage',
 'Facilities - Med Mooring',
 'Facilities - Beach Mooring',
 'Facilities - Ice Mooring',
 'Facilities - Ro-Ro',
 'Facilities - Solid Bulk',
 'Facilities - Liquid Bulk',
 'Facilities - Container',
 'Facilities - Breakbulk',
 'Facilities - Oil Terminal',
 'Facilities - LNG Terminal',
 'Facilities - Other',
 'Medical Facilities',
 'Garbage Disposal',
 'Chemical Holding Tank Disposal',
 'Degaussing',
 'Dirty Ballast Disposal',
 'Cranes - Fixed',
 'Cranes - Mobile',
 'Cranes - Floating',
 'Cranes - Container',
 'Lifts - 100+ Tons',
 'Lifts - 50-100 Tons',
 'Lifts - 25-49 Tons',
 'Lifts - 0-24 Tons',
 'Services - Longshoremen',
 'Services - Electricity',
 'Services - Steam',
 'Services - Navigation Equipment',
 'Services - Electrical Repair',
 'Services - Ice Breaking',
 'Services - Diving',
 'Supplies - Provisions',
 'Supplies - Potable Water',
 'Supplies - Fuel Oil',
 'Supplies - Diesel Oil',
 'Supplies - Aviation Fuel',
 'Supplies - Deck',
 'Supplies - Engine',
 'Repairs',
 'Dry Dock',
 'Railway',
 'Latitude',
 'Longitude']
In [4]:
#Cambiamos el nombre de las columnas
infoseaports.rename(columns={'Main Port Name':'name'},inplace=True)
infoseaports.rename(columns={'Country Code':'CountryCode'},inplace=True)
In [5]:
infoseaports=infoseaports.loc[:,['name', 'CountryCode','Latitude', 'Longitude']]
infoseaports.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3774 entries, 0 to 3773
Data columns (total 4 columns):
 #   Column       Non-Null Count  Dtype  
---  ------       --------------  -----  
 0   name         3774 non-null   object 
 1   CountryCode  3774 non-null   object 
 2   Latitude     3774 non-null   float64
 3   Longitude    3774 non-null   float64
dtypes: float64(2), object(2)
memory usage: 118.1+ KB
In [6]:
seaports=gpd.GeoDataFrame(data=infoseaports.copy(),
                 geometry=gpd.points_from_xy(infoseaports.Longitude,
                                             infoseaports.Latitude), 
                 crs=4326)#le ponemos alguna proyección

seaports_ukr=seaports[seaports['CountryCode']=='Ukraine'].copy()

seaports_ukr.reset_index(drop=True, inplace=True)

seaports_ukr_6381=seaports_ukr.to_crs(6381) # proyectamos correctamente
In [7]:
#Observamos que Ukraina tiene puertos marinos
seaports[seaports.CountryCode=='Ukraine']
Out[7]:
name CountryCode Latitude Longitude geometry
39 Kyrylivka Ukraine 46.350000 35.366667 POINT (35.36667 46.35000)
57 Henichesk Ukraine 46.166667 34.816667 POINT (34.81667 46.16667)
92 Balaklava Ukraine 44.500000 33.600000 POINT (33.60000 44.50000)
93 Alushta Ukraine 44.683333 34.416667 POINT (34.41667 44.68333)
183 Sudak Ukraine 44.850000 34.983333 POINT (34.98333 44.85000)
425 Ust-Dunaisk Ukraine 45.466667 29.700000 POINT (29.70000 45.46667)
1104 Mariupol Ukraine 47.083333 37.566667 POINT (37.56667 47.08333)
1105 Berdyansk Ukraine 46.750000 36.783333 POINT (36.78333 46.75000)
1148 Mykolayiv Ukraine 46.950000 31.983333 POINT (31.98333 46.95000)
1180 Izmayil Ukraine 45.333333 28.850000 POINT (28.85000 45.33333)
1211 Reni Ukraine 45.433333 28.300000 POINT (28.30000 45.43333)
1458 Kherson Ukraine 46.616667 32.600000 POINT (32.60000 46.61667)
1459 Odesa Ukraine 46.483333 30.733333 POINT (30.73333 46.48333)
1671 Dnipro-Buzkyy Ukraine 46.733333 31.883333 POINT (31.88333 46.73333)
1673 Khorly Ukraine 46.083333 33.283333 POINT (33.28333 46.08333)
1795 Chornomors Ke Ukraine 45.516667 32.700000 POINT (32.70000 45.51667)
2312 Kerch Ukraine 45.350000 36.483333 POINT (36.48333 45.35000)
2313 Feodosiya Ukraine 45.016667 35.433333 POINT (35.43333 45.01667)
2314 Illichivsk Ukraine 46.300000 30.650000 POINT (30.65000 46.30000)
2329 Belgorod-Dnestrovsky Ukraine 46.183333 30.366667 POINT (30.36667 46.18333)
2338 Port Oktyabrsk Ukraine 46.833333 31.933333 POINT (31.93333 46.83333)
2725 Yevpatoriya Ukraine 45.200000 33.383333 POINT (33.38333 45.20000)
2757 Yalta Ukraine 44.483333 34.166667 POINT (34.16667 44.48333)
2803 Yuzhnyy Ukraine 46.600000 31.016667 POINT (31.01667 46.60000)
2832 Skadovs'k Ukraine 46.100000 32.916667 POINT (32.91667 46.10000)
2881 Sevastopol Ukraine 44.616667 33.533333 POINT (33.53333 44.61667)
In [8]:
#Ejercicio 1
infoairports=pd.read_csv(os.path.join("data","ua-airports.csv"))

#al igual que el otro caso, este también tiene muchas columnas
infoairports.columns.to_list()
Out[8]:
['id',
 'ident',
 'type',
 'name',
 'latitude_deg',
 'longitude_deg',
 'elevation_ft',
 'continent',
 'country_name',
 'iso_country',
 'region_name',
 'iso_region',
 'local_region',
 'municipality',
 'scheduled_service',
 'gps_code',
 'iata_code',
 'local_code',
 'home_link',
 'wikipedia_link',
 'keywords',
 'score',
 'last_updated']
In [9]:
#Cambiaremos el nombre de las columnas y solo nos quedaremos con algunas
#Cambiamos el nombre de las columnas
infoairports.rename(columns={'name':'airportName'},inplace=True)
infoairports.rename(columns={'country_name':'Country'},inplace=True)
infoairports=infoairports.loc[:,['airportName', 'Country','latitude_deg', 'longitude_deg']]
infoairports.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 247 entries, 0 to 246
Data columns (total 4 columns):
 #   Column         Non-Null Count  Dtype  
---  ------         --------------  -----  
 0   airportName    247 non-null    object 
 1   Country        247 non-null    object 
 2   latitude_deg   247 non-null    float64
 3   longitude_deg  247 non-null    float64
dtypes: float64(2), object(2)
memory usage: 7.8+ KB
In [10]:
infoairports
Out[10]:
airportName Country latitude_deg longitude_deg
0 Boryspil International Airport Ukraine 50.345001 30.894699
1 Ihor Sikorsky Kyiv International Airport (Zhul... Ukraine 50.401940 30.451940
2 Odessa International Airport Ukraine 46.426800 30.676500
3 Lviv International Airport Ukraine 49.812500 23.956100
4 Simferopol International Airport Ukraine 45.052200 33.975101
... ... ... ... ...
242 Oreanda Heliport Ukraine 44.451300 34.129300
243 Pension Wisteria Helipad Ukraine 44.461824 34.145346
244 Massandra Palace Heliport Ukraine 44.514500 34.203900
245 Artek Heliport Ukraine 44.560590 34.307563
246 Palmira Airfield Ukraine 49.763000 32.123000

247 rows × 4 columns

In [11]:
airports=gpd.GeoDataFrame(data=infoairports.copy(),
                 geometry=gpd.points_from_xy(infoairports.longitude_deg,
                                             infoairports.latitude_deg), 
                 crs=4326)

airports_ukr=airports[airports['Country']=='Ukraine'].copy()

airports_ukr.reset_index(drop=True, inplace=True)
#Lo proyectamos correctamente
airports_ukr_6381=airports_ukr.to_crs(6381) 
airports_ukr_6381
Out[11]:
airportName Country latitude_deg longitude_deg geometry
0 Boryspil International Airport Ukraine 50.345001 30.894699 POINT (1003781.802 5626341.710)
1 Ihor Sikorsky Kyiv International Airport (Zhul... Ukraine 50.401940 30.451940 POINT (971541.639 5628534.004)
2 Odessa International Airport Ukraine 46.426800 30.676500 POINT (1043729.138 5189358.444)
3 Lviv International Airport Ukraine 49.812500 23.956100 POINT (512870.058 5524313.763)
4 Simferopol International Airport Ukraine 45.052200 33.975101 POINT (1322174.059 5073484.910)
... ... ... ... ... ...
242 Oreanda Heliport Ukraine 44.451300 34.129300 POINT (1345282.698 5008706.266)
243 Pension Wisteria Helipad Ukraine 44.461824 34.145346 POINT (1346368.815 5010084.753)
244 Massandra Palace Heliport Ukraine 44.514500 34.203900 POINT (1350066.889 5016703.423)
245 Artek Heliport Ukraine 44.560590 34.307563 POINT (1357460.435 5023187.276)
246 Palmira Airfield Ukraine 49.763000 32.123000 POINT (1100653.888 5574277.340)

247 rows × 5 columns

In [12]:
airports_ukr_6381.info()

<class 'geopandas.geodataframe.GeoDataFrame'>
RangeIndex: 247 entries, 0 to 246
Data columns (total 5 columns):
 #   Column         Non-Null Count  Dtype   
---  ------         --------------  -----   
 0   airportName    247 non-null    object  
 1   Country        247 non-null    object  
 2   latitude_deg   247 non-null    float64 
 3   longitude_deg  247 non-null    float64 
 4   geometry       247 non-null    geometry
dtypes: float64(2), geometry(1), object(2)
memory usage: 9.8+ KB
In [13]:
seaports_ukr_6381.info()

<class 'geopandas.geodataframe.GeoDataFrame'>
RangeIndex: 26 entries, 0 to 25
Data columns (total 5 columns):
 #   Column       Non-Null Count  Dtype   
---  ------       --------------  -----   
 0   name         26 non-null     object  
 1   CountryCode  26 non-null     object  
 2   Latitude     26 non-null     float64 
 3   Longitude    26 non-null     float64 
 4   geometry     26 non-null     geometry
dtypes: float64(2), geometry(1), object(2)
memory usage: 1.1+ KB
In [14]:
seaports_ukr_6381
Out[14]:
name CountryCode Latitude Longitude geometry
0 Kyrylivka Ukraine 46.350000 35.366667 POINT (1405336.698 5236418.258)
1 Henichesk Ukraine 46.166667 34.816667 POINT (1366695.030 5208397.526)
2 Balaklava Ukraine 44.500000 33.600000 POINT (1302296.116 5007378.718)
3 Alushta Ukraine 44.683333 34.416667 POINT (1363843.500 5038272.413)
4 Sudak Ukraine 44.850000 34.983333 POINT (1405518.784 5064492.300)
5 Ust-Dunaisk Ukraine 45.466667 29.700000 POINT (980454.487 5073894.209)
6 Mariupol Ukraine 47.083333 37.566667 POINT (1556680.337 5351496.468)
7 Berdyansk Ukraine 46.750000 36.783333 POINT (1505041.032 5301969.521)
8 Mykolayiv Ukraine 46.950000 31.983333 POINT (1135883.406 5260702.436)
9 Izmayil Ukraine 45.333333 28.850000 POINT (915449.001 5052187.180)
10 Reni Ukraine 45.433333 28.300000 POINT (871327.266 5059222.393)
11 Kherson Ukraine 46.616667 32.600000 POINT (1188294.140 5230541.080)
12 Odesa Ukraine 46.483333 30.733333 POINT (1047313.434 5196178.421)
13 Dnipro-Buzkyy Ukraine 46.733333 31.883333 POINT (1131655.225 5235574.118)
14 Khorly Ukraine 46.083333 33.283333 POINT (1249889.275 5179369.358)
15 Chornomors Ke Ukraine 45.516667 32.700000 POINT (1214161.455 5109537.517)
16 Kerch Ukraine 45.350000 36.483333 POINT (1513161.551 5142005.325)
17 Feodosiya Ukraine 45.016667 35.433333 POINT (1437716.799 5089358.181)
18 Illichivsk Ukraine 46.300000 30.650000 POINT (1043427.095 5175023.067)
19 Belgorod-Dnestrovsky Ukraine 46.183333 30.366667 POINT (1023157.402 5159421.608)
20 Port Oktyabrsk Ukraine 46.833333 31.933333 POINT (1133909.093 5247212.287)
21 Yevpatoriya Ukraine 45.200000 33.383333 POINT (1273016.638 5082483.822)
22 Yalta Ukraine 44.483333 34.166667 POINT (1347674.081 5012753.174)
23 Yuzhnyy Ukraine 46.600000 31.016667 POINT (1067389.611 5211879.691)
24 Skadovs'k Ukraine 46.100000 32.916667 POINT (1221277.538 5176844.654)
25 Sevastopol Ukraine 44.616667 33.533333 POINT (1294970.615 5019516.120)
In [15]:
#ahora los graficaremos
base=airports_ukr_6381.plot(color='orange',marker="^")
seaports_ukr_6381.plot(ax=base,color='black', alpha=1,markersize=3)
Out[15]:
<Axes: >
In [16]:
seaports_ukr_6381.head()
Out[16]:
name CountryCode Latitude Longitude geometry
0 Kyrylivka Ukraine 46.350000 35.366667 POINT (1405336.698 5236418.258)
1 Henichesk Ukraine 46.166667 34.816667 POINT (1366695.030 5208397.526)
2 Balaklava Ukraine 44.500000 33.600000 POINT (1302296.116 5007378.718)
3 Alushta Ukraine 44.683333 34.416667 POINT (1363843.500 5038272.413)
4 Sudak Ukraine 44.850000 34.983333 POINT (1405518.784 5064492.300)
In [17]:
#Ahora calcularemos la distancia entre los dos primeros puntos de los gdf en km
#Estos son Boryspil International Airport y Kyrylivka
airports_ukr_6381.iloc[0].geometry.distance(seaports_ukr_6381.iloc[0].geometry)/1000
Out[17]:
559.7201380700092
In [18]:
#Calculamos las distancias entre cada airport y seaport
seaports_ukr_6381.geometry.apply\
(lambda g: airports_ukr_6381.geometry.distance(g)/1000)
Out[18]:
0 1 2 3 4 5 6 7 8 9 ... 237 238 239 240 241 242 243 244 245 246
0 559.720138 584.750298 364.656898 937.752912 182.929769 227.246018 409.397491 1023.660366 266.553605 745.648828 ... 247.426723 247.845160 249.109343 248.764635 248.119164 235.497844 233.889005 226.559839 218.539672 454.950958
1 553.519063 576.767599 323.526590 910.395602 142.068754 247.832940 438.265722 990.222043 311.155029 712.969227 ... 211.059080 211.270161 212.073052 211.761947 211.519416 200.835972 199.351727 192.413940 185.440326 452.378081
2 687.187007 703.727514 316.185868 943.618219 69.030148 449.708176 645.121316 986.240433 516.681170 723.768680 ... 29.852960 28.314467 24.853887 25.101139 28.132493 43.007076 44.155695 48.672342 57.384776 601.692311
3 689.543273 708.737960 353.977674 979.995915 54.555131 417.379058 608.264756 1032.317910 462.281028 764.642633 ... 49.986742 50.979404 53.575303 53.162646 51.297762 34.909317 33.164872 25.593287 16.380014 597.134871
4 690.700632 711.673525 382.731370 1004.120274 83.828457 395.524515 581.292953 1063.281628 422.807817 792.530033 ... 98.107152 99.262658 102.148642 101.732165 99.583457 82.100351 80.367282 73.203070 63.369629 593.989387
5 552.939785 554.711403 131.664996 649.240305 341.719817 526.667305 706.678273 666.822102 685.589132 421.846950 ... 358.479698 356.930368 353.409052 353.680704 356.736324 370.606383 371.436323 374.010847 380.400681 514.617503
6 617.443680 647.407980 537.966236 1058.019714 363.708153 236.797661 335.367634 1164.071298 113.044232 886.816941 ... 417.270331 418.071368 420.169884 419.776937 418.379389 402.733267 400.989894 393.415175 384.025383 507.534668
7 597.057898 625.512561 474.857787 1016.779329 292.652605 222.427849 360.704170 1115.268081 166.593791 837.114370 ... 348.098852 348.834568 350.793235 350.407021 349.138010 333.955180 332.225210 324.644008 315.435528 487.524883
8 388.771029 402.875016 116.543443 676.488406 264.110980 284.674718 464.467537 753.789224 456.183670 476.321122 ... 325.553009 324.565310 322.524314 322.516119 324.588984 327.643302 327.281729 324.669190 324.822769 315.547682
9 580.909725 579.069983 187.807745 620.462180 407.282293 588.102706 763.480321 621.869504 751.644588 393.282041 ... 419.076432 417.510465 413.927208 414.224414 417.295882 432.027310 432.971708 436.063992 442.961739 553.966593
10 582.381768 578.064556 216.004160 587.198052 451.072334 616.432153 786.718826 581.279041 785.282122 361.491684 ... 463.732124 462.166611 458.585269 458.881545 461.952800 476.639938 477.576152 480.624063 487.466910 563.801648
11 436.695480 453.188719 150.316497 736.546048 206.374594 273.193456 464.086700 810.857921 425.677561 534.169388 ... 271.017515 270.141770 268.379971 268.333778 270.193829 271.764773 271.272178 268.136095 267.605746 354.732901
12 432.360334 438.945002 7.704497 627.138362 301.001762 393.663075 568.722805 682.144933 564.518735 411.194798 ... 344.976258 343.650768 340.755267 340.881445 343.571177 352.039048 352.228582 351.953021 355.129692 381.842895
13 411.158027 424.327506 99.332197 682.836485 250.140635 305.320035 487.775885 754.359541 471.611116 478.069521 ... 308.546621 307.487516 305.270565 305.287283 307.492012 311.617906 311.363741 309.205492 309.993812 340.119032
14 510.248148 528.418666 206.401996 813.746871 128.205328 291.344497 488.597483 882.128544 409.429816 607.287359 ... 196.684082 195.985310 194.664265 194.562075 196.078470 195.514184 194.847578 191.038637 189.642814 422.165271
15 557.984026 572.906387 188.198181 814.769267 113.870598 369.138259 566.064760 867.461151 484.312698 598.874052 ... 160.154318 158.968561 156.448072 156.509340 158.936689 165.407743 165.437717 164.585710 167.304996 478.400534
16 702.886522 728.053765 471.814697 1070.860781 202.907046 356.034450 517.211435 1147.018653 323.364405 870.832997 ... 230.531764 231.736902 234.704788 234.288135 232.057220 214.364056 212.656658 205.670697 195.858536 597.512902
17 690.399082 712.762125 406.480417 1022.021454 116.627979 377.678612 557.928445 1086.843388 389.385541 813.918880 ... 138.745178 139.916079 142.823200 142.406653 140.236805 122.673529 120.949289 113.847357 104.017656 590.557361
18 453.056582 459.172831 14.338559 635.212374 296.664570 410.725839 587.908039 684.759183 578.215511 416.552562 ... 336.737316 335.364777 332.345731 332.495042 335.267160 344.641964 344.932360 345.098643 348.813770 403.334700
19 467.321941 471.943458 36.323691 627.327234 311.120679 436.196762 612.582779 670.741910 603.578027 405.931746 ... 346.793330 345.371231 342.219130 342.395262 345.252714 355.640015 356.043696 356.704770 360.996275 422.031971
20 400.839409 414.450771 107.142389 680.054933 256.173572 295.454337 476.790635 754.278651 464.094374 477.378685 ... 316.096939 315.072278 312.940432 312.944962 315.086156 318.690952 318.384360 316.004002 316.484451 328.751362
21 606.851546 623.745121 252.972217 879.224954 49.974318 379.344524 576.425661 931.924269 468.040606 663.649310 ... 100.733396 99.784256 97.885047 97.853511 99.819632 103.273962 103.063898 101.310424 103.183503 521.123577
22 703.386659 721.568877 351.528021 979.077113 65.868011 442.433060 634.768640 1026.230545 492.112502 761.274719 ... 20.552062 21.790392 24.933993 24.520677 22.109304 4.700658 2.970554 4.618441 14.305356 613.456082
23 419.314582 427.536724 32.665341 636.480152 289.945220 368.216333 544.050035 697.245894 539.415033 423.980508 ... 338.238882 336.977735 334.249046 334.345922 336.920807 344.244112 344.311767 343.511600 346.043221 363.921102
24 499.351578 516.131076 177.988846 789.034815 144.441492 304.092410 500.251000 854.996044 432.137999 580.812253 ... 208.001012 207.124229 205.367961 205.320393 207.176326 208.920553 208.462688 205.504041 205.320168 415.334570
25 673.073712 689.571668 303.263408 930.860860 60.437221 438.379092 634.236379 974.816919 509.534457 711.499636 ... 41.089661 39.679051 36.615195 36.766147 39.568901 51.460263 52.256346 55.168022 62.597564 587.808644

26 rows × 247 columns

In [19]:
airports_ukr_6381.columns.to_list()
Out[19]:
['airportName', 'Country', 'latitude_deg', 'longitude_deg', 'geometry']
In [20]:
#Ahora les agregamos los nombres y los ordenamos
seaports_ukr_6381.set_index('name').geometry.apply\
(lambda g: airports_ukr_6381.set_index('airportName').geometry.distance(g)/1000).\
sort_index(axis=0).sort_index(axis=1)
Out[20]:
airportName Aeroclub Swallow Aerodrom Belz Aerodrom Krupske Anan'iv Airstrip Andrushivka Artek Heliport Artsyz Air Base Askaniya-Nova Airport Bagerovo Air Base Bekhtery Airfield ... Zabroshennyy Airport Zahnitkiv Airstrip Zaporizhzhia International Airport Zavodskoe Airfield Zhalizhnia Zhovti Vody Airstrip Zhovtneve Air Base Zhovtneve Air Base 2 Zhytomyr Airport Zmiyinyy Island Helipad
name
Alushta 793.344805 1014.189778 953.813304 482.865583 726.779793 16.380014 423.132934 203.003618 167.561082 242.002305 ... 644.964503 567.985510 365.656135 38.920587 991.230881 419.449455 468.103031 1022.614899 760.114035 341.896252
Balaklava 756.473368 980.946736 915.585308 455.348951 711.026709 57.384776 371.635860 216.193197 235.216366 220.420538 ... 631.767378 537.203484 402.233095 60.123468 959.880667 433.070192 411.593580 993.529179 744.409898 283.944571
Belgorod-Dnestrovsky 440.355431 667.261024 598.316045 170.126798 440.918327 360.996275 81.478268 262.376314 470.349767 149.844245 ... 376.281182 234.349099 424.312562 324.001570 648.510922 337.850851 145.606270 685.104864 472.631817 104.562559
Berdyansk 844.527379 1034.129326 1000.999267 532.265756 688.475123 315.435528 583.148651 240.729842 157.722822 354.223100 ... 605.374555 616.160182 169.197860 297.821580 1003.402925 312.217269 644.621095 1022.491084 718.181171 542.266264
Chornomors Ke 627.929841 850.015364 788.212387 321.309027 576.431487 167.304996 265.005093 129.443496 281.319235 86.425402 ... 497.825605 404.581182 333.037175 127.398920 827.907405 323.409245 317.052138 860.554360 609.797433 199.451843
Dnipro-Buzkyy 498.494917 713.301982 659.590342 180.549322 426.097273 309.993812 213.321370 146.870038 372.867843 64.526537 ... 347.186841 267.758489 291.757361 266.065567 688.843970 216.817484 277.968368 718.850713 459.484935 211.197650
Feodosiya 837.270327 1051.937950 998.397347 519.573819 744.415044 104.017656 489.399951 207.802328 78.409398 283.215364 ... 660.507655 606.947912 321.731381 110.212882 1026.644062 405.841334 539.666983 1054.896695 777.279570 416.796801
Henichesk 729.430179 935.758833 889.782531 409.619441 614.611404 185.440326 425.487246 89.846018 141.710842 197.253405 ... 530.105330 497.178802 195.507126 152.580730 908.417314 267.284114 484.627064 933.764811 646.985618 377.023373
Illichivsk 448.065602 673.281431 607.338387 162.943366 433.867208 348.813770 106.619752 239.184582 450.870968 127.825964 ... 366.082030 234.292672 398.757955 310.218425 653.303552 313.402579 171.031777 688.656901 466.103494 121.995439
Izmayil 443.647608 670.628865 585.297355 275.947552 523.381102 442.961739 79.898173 400.353625 585.184091 287.630612 ... 475.698779 301.752638 574.699895 416.128404 659.849761 488.500424 37.040980 702.703350 551.318742 106.934437
Kerch 889.133415 1096.564989 1049.768258 569.226562 772.588450 195.858536 563.860318 248.538193 20.065147 344.861263 ... 687.953389 656.954966 298.461301 199.337171 1069.203233 411.841947 617.738702 1094.290371 804.569937 498.487645
Kherson 553.183144 765.426387 714.137775 233.787058 466.425801 267.605746 261.239656 90.008256 316.836221 49.341836 ... 384.795992 321.513696 251.104415 222.749969 740.040518 205.041207 324.720205 768.652335 499.758883 241.662050
Khorly 629.205629 843.931487 790.326858 311.345152 545.892455 189.642814 305.297906 51.178537 245.845821 79.135546 ... 463.721685 398.667276 254.606346 144.661376 819.058858 255.067390 364.284262 848.216474 579.179218 259.376510
Kyrylivka 759.179243 960.639546 918.637407 440.581746 630.666671 218.539672 469.318415 128.213926 127.075424 240.135404 ... 546.048471 527.378560 171.151697 191.308975 932.178364 268.987687 529.414688 955.629022 662.381380 423.841296
Mariupol 890.449589 1071.894894 1044.363651 584.270071 719.387922 384.025383 648.178633 307.294525 216.311369 420.418141 ... 638.230583 665.688644 193.913662 368.394755 1039.926238 344.831356 710.524495 1056.268660 747.595102 611.147154
Mykolayiv 493.698005 705.002952 654.497941 173.903820 409.147183 324.822769 230.826227 147.159113 375.751868 83.992506 ... 328.834969 261.687347 274.404817 280.316726 679.570758 192.311322 295.742347 708.271016 442.538724 235.074577
Odesa 440.143613 663.680723 600.244484 146.079689 416.124104 355.129692 121.245639 232.063663 448.925749 124.161489 ... 346.933401 221.387518 383.730931 315.164477 642.785086 293.921301 186.165623 677.192687 448.591893 143.504210
Port Oktyabrsk 496.393169 709.616025 657.389536 177.314979 418.323876 316.484451 221.482087 146.162610 373.706306 72.933274 ... 338.738879 264.930106 283.321589 272.247847 684.700242 205.311560 286.298964 714.101777 451.721334 222.360082
Reni 414.581152 639.158017 551.056436 281.848306 514.582290 487.466910 101.857038 438.032421 627.793461 324.670167 ... 473.330386 294.382398 606.165605 460.178641 630.207783 512.139829 37.071214 674.186984 540.927305 151.085640
Sevastopol 743.728401 967.879547 903.032427 441.682223 696.931283 62.597564 360.977927 203.392957 234.505138 206.312936 ... 617.618310 523.807176 391.610889 54.480091 946.641814 419.809208 402.251372 980.114391 730.316484 274.902448
Skadovs'k 603.905471 820.257838 765.023902 287.481134 528.412605 205.320168 276.711751 72.554636 273.893216 50.924112 ... 447.282633 374.299067 271.394118 160.683472 795.968949 256.017064 336.033599 825.956932 561.783224 233.349315
Sudak 818.331829 1036.005491 979.313474 503.256716 737.226945 63.369629 459.866471 202.860257 118.879866 263.456814 ... 654.095897 589.866691 341.240976 74.153894 1011.752587 411.736879 507.860609 1041.450852 770.359895 383.289805
Ust-Dunaisk 466.426307 695.555617 616.288609 248.247036 511.431974 380.400681 59.223853 332.377537 517.684933 220.175140 ... 454.727387 293.042427 510.504834 351.328496 681.379498 432.437071 83.117727 721.845441 541.467571 46.015765
Yalta 792.068949 1014.853180 951.935429 485.716118 735.231155 14.305356 413.466555 220.751699 196.484848 246.363178 ... 654.395119 569.464059 391.759229 49.870764 992.807484 438.622051 455.357174 1025.292163 768.620158 328.038017
Yevpatoriya 692.476627 913.965050 852.861974 383.799522 633.881730 103.183503 326.150134 139.794662 228.874277 144.238518 ... 553.649508 468.072936 335.700222 62.686519 891.456679 354.132289 374.956150 923.526368 667.279140 252.183924
Yuzhnyy 450.007176 671.102533 610.763015 144.963341 411.059024 346.043221 146.722766 210.777233 431.154778 107.116558 ... 338.830959 225.866557 358.358913 304.706084 649.044726 269.461352 211.646594 682.133176 443.927337 163.349539

26 rows × 247 columns

In [21]:
seaports_ukr_6381.iloc[0]
Out[21]:
name                                             Kyrylivka
CountryCode                                        Ukraine
Latitude                                             46.35
Longitude                                        35.366667
geometry       POINT (1405336.697623667 5236418.258094744)
Name: 0, dtype: object
In [22]:
#Lo relacionamos a una variable
distanceMatrixKM_sea_air= seaports_ukr_6381.set_index('name').geometry.apply\
                          (lambda g: airports_ukr_6381.set_index('airportName').geometry.distance(g)/1000).\
                          sort_index(axis=0).sort_index(axis=1)
In [23]:
#La distancia de un seaport a todos los aeropuertos
distanceMatrixKM_sea_air.mean(axis=1).sort_values(ascending=True)
Out[23]:
name
Mykolayiv               372.892895
Port Oktyabrsk          376.172623
Dnipro-Buzkyy           379.317965
Kherson                 384.235610
Yuzhnyy                 390.166449
Odesa                   398.740574
Skadovs'k               405.545644
Illichivsk              408.468591
Khorly                  409.781221
Belgorod-Dnestrovsky    419.408929
Chornomors Ke           434.779477
Henichesk               444.262682
Yevpatoriya             457.736537
Kyrylivka               458.556306
Ust-Dunaisk             476.245767
Sevastopol              499.494761
Balaklava               509.657660
Izmayil                 509.668873
Berdyansk               512.995943
Alushta                 513.366295
Sudak                   521.080072
Yalta                   521.575171
Reni                    522.313310
Feodosiya               527.939146
Mariupol                548.093237
Kerch                   557.511879
dtype: float64
In [24]:
#Mostramos la media, la distancia mínima y máxima
SomeStats=pd.DataFrame()
SomeStats['mean']=distanceMatrixKM_sea_air.mean(axis=1)
SomeStats['min']=distanceMatrixKM_sea_air.min(axis=1)
SomeStats['max']=distanceMatrixKM_sea_air.max(axis=1)
SomeStats.head()
Out[24]:
mean min max
name
Alushta 513.366295 3.885283 1032.317910
Balaklava 509.657660 1.224485 993.529179
Belgorod-Dnestrovsky 419.408929 36.323691 739.484540
Berdyansk 512.995943 7.611671 1115.268081
Chornomors Ke 434.779477 35.034855 867.461151
In [25]:
#Aquí mostramos los aeropuertos más lejanos a cada seaport
distanceMatrixKM_sea_air.idxmax(axis="columns")
Out[25]:
name
Alushta                 Uzhhorod International Airport
Balaklava                         Zhovtneve Air Base 2
Belgorod-Dnestrovsky            Gostra Mogila Airfield
Berdyansk               Uzhhorod International Airport
Chornomors Ke           Uzhhorod International Airport
Dnipro-Buzkyy           Uzhhorod International Airport
Feodosiya               Uzhhorod International Airport
Henichesk               Uzhhorod International Airport
Illichivsk                      Gostra Mogila Airfield
Izmayil                         Gostra Mogila Airfield
Kerch                   Uzhhorod International Airport
Kherson                 Uzhhorod International Airport
Khorly                  Uzhhorod International Airport
Kyrylivka               Uzhhorod International Airport
Mariupol                Uzhhorod International Airport
Mykolayiv               Uzhhorod International Airport
Odesa                           Gostra Mogila Airfield
Port Oktyabrsk          Uzhhorod International Airport
Reni                            Gostra Mogila Airfield
Sevastopol                        Zhovtneve Air Base 2
Skadovs'k               Uzhhorod International Airport
Sudak                   Uzhhorod International Airport
Ust-Dunaisk                     Gostra Mogila Airfield
Yalta                   Uzhhorod International Airport
Yevpatoriya             Uzhhorod International Airport
Yuzhnyy                 Uzhhorod International Airport
dtype: object
In [26]:
#los seaports más lejanos a cada aeropuerto son:
distanceMatrixKM_sea_air.idxmax(axis="rows")
Out[26]:
airportName
Aeroclub Swallow           Mariupol
Aerodrom Belz                 Kerch
Aerodrom Krupske              Kerch
Anan'iv Airstrip           Mariupol
Andrushivka                   Kerch
                             ...   
Zhovti Vody Airstrip           Reni
Zhovtneve Air Base         Mariupol
Zhovtneve Air Base 2          Kerch
Zhytomyr Airport              Kerch
Zmiyinyy Island Helipad    Mariupol
Length: 247, dtype: object
In [27]:
#los aeropuertos más cercanos a cada seaport
distanceMatrixKM_sea_air.idxmin(axis="columns")
Out[27]:
name
Alushta                                    Profug Heliport
Balaklava                     Demetrynskaya Street Helipad
Belgorod-Dnestrovsky          Odessa International Airport
Berdyansk                                Berdyansk Airport
Chornomors Ke                            Donuzlav Air Base
Dnipro-Buzkyy                             Ochakiv Air Base
Feodosiya                        Gora Klementyeva Airfield
Henichesk                               Genichesk Air Base
Illichivsk                    Odessa International Airport
Izmayil                       Izmail International Airport
Kerch                                        Kerch Airport
Kherson                      Kherson International Airport
Khorly                                  Pryvillia Airfield
Kyrylivka                               Genichesk Air Base
Mariupol                    Mariupol International Airport
Mykolayiv                               Kulbakyne Air Base
Odesa                         Odessa International Airport
Port Oktyabrsk                          Kulbakyne Air Base
Reni                                         Reni Heliport
Sevastopol              Sevastopol Naval Institute Helipad
Skadovs'k                                Skadovsk Airfield
Sudak                              Koktebel Gliding Center
Ust-Dunaisk                                 Kiliya Airport
Yalta                                       Yalta Heliport
Yevpatoriya                            Yevpatoriya Airport
Yuzhnyy                                    Yuzhne Heliport
dtype: object
In [28]:
#el seaport más cercano a cada aeropuerto
distanceMatrixKM_sea_air.idxmin(axis="rows")
Out[28]:
airportName
Aeroclub Swallow                  Reni
Aerodrom Belz                     Reni
Aerodrom Krupske                  Reni
Anan'iv Airstrip               Yuzhnyy
Andrushivka                  Mykolayiv
                              ...     
Zhovti Vody Airstrip         Mykolayiv
Zhovtneve Air Base             Izmayil
Zhovtneve Air Base 2              Reni
Zhytomyr Airport             Mykolayiv
Zmiyinyy Island Helipad    Ust-Dunaisk
Length: 247, dtype: object
In [29]:
mins=distanceMatrixKM_sea_air.idxmin(axis="columns")
mins
Out[29]:
name
Alushta                                    Profug Heliport
Balaklava                     Demetrynskaya Street Helipad
Belgorod-Dnestrovsky          Odessa International Airport
Berdyansk                                Berdyansk Airport
Chornomors Ke                            Donuzlav Air Base
Dnipro-Buzkyy                             Ochakiv Air Base
Feodosiya                        Gora Klementyeva Airfield
Henichesk                               Genichesk Air Base
Illichivsk                    Odessa International Airport
Izmayil                       Izmail International Airport
Kerch                                        Kerch Airport
Kherson                      Kherson International Airport
Khorly                                  Pryvillia Airfield
Kyrylivka                               Genichesk Air Base
Mariupol                    Mariupol International Airport
Mykolayiv                               Kulbakyne Air Base
Odesa                         Odessa International Airport
Port Oktyabrsk                          Kulbakyne Air Base
Reni                                         Reni Heliport
Sevastopol              Sevastopol Naval Institute Helipad
Skadovs'k                                Skadovsk Airfield
Sudak                              Koktebel Gliding Center
Ust-Dunaisk                                 Kiliya Airport
Yalta                                       Yalta Heliport
Yevpatoriya                            Yevpatoriya Airport
Yuzhnyy                                    Yuzhne Heliport
dtype: object
In [30]:
matrix1=airports_ukr_6381[airports_ukr_6381.airportName.str.contains('Profug Heliport')]
matrix1
Out[30]:
airportName Country latitude_deg longitude_deg geometry
181 Profug Heliport Ukraine 44.6511 34.3995 POINT (1363082.450 5034462.396)
In [31]:
distanceMatrixKM_sea_air2= matrix1.set_index('airportName').geometry.apply\
                          (lambda g: seaports_ukr_6381.set_index('name').geometry.distance(g)/1000).\
                          sort_index(axis=0).sort_index(axis=1)
distanceMatrixKM_sea_air2
Out[31]:
name Alushta Balaklava Belgorod-Dnestrovsky Berdyansk Chornomors Ke Dnipro-Buzkyy Feodosiya Henichesk Illichivsk Izmayil ... Odesa Port Oktyabrsk Reni Sevastopol Skadovs'k Sudak Ust-Dunaisk Yalta Yevpatoriya Yuzhnyy
airportName
Profug Heliport 3.885283 66.547006 362.165491 302.840388 166.774508 306.601509 92.648979 173.972642 349.194571 447.984232 ... 354.770551 312.702644 492.378126 69.73244 200.95109 51.986898 384.654424 26.621573 102.068153 344.834963

1 rows × 26 columns

In [32]:
mins2=distanceMatrixKM_sea_air2.idxmin(axis="columns")
mins2
Out[32]:
airportName
Profug Heliport    Alushta
dtype: object
In [33]:
base=seaports_ukr_6381[seaports_ukr_6381.name.str.contains('Alushta')].explore(color='red', marker_kwds=dict(radius=10))
# Los más cercanos los graficamos de rojo
airports_ukr_6381[airports_ukr_6381.airportName.str.contains('Profug Heliport')].explore(m=base,color='orange',marker_kwds=dict(radius=10))
Out[33]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [34]:
base=seaports_ukr_6381.explore(color='black')
# Los más cercanos los graficamos de rojo
airports_ukr_6381[airports_ukr_6381.airportName.isin(mins)].explore(m=base,color='red',marker_kwds=dict(radius=5))
Out[34]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [35]:
#Ejercicio 2
In [36]:
#Proyectamos los ríos de Ukrania
rios_ukr_638=hidrografia.to_crs(6381)
In [37]:
#Elegimos Dniester
rios_ukr_638[rios_ukr_638.NOMBRE.str.contains('Dniester')]
Out[37]:
NOMBRE geometry
1 Dniester MULTILINESTRING ((438289.939 5451514.632, 4388...
In [38]:
#La distancia de este río a cada aeropuerto
rios_ukr_638[rios_ukr_638.NOMBRE.str.contains('Dniester')].iloc[0].geometry.distance(airports_ukr_6381.geometry)
Out[38]:
0      298950.269541
1      285244.694554
2       26821.563990
3       33079.935095
4      299062.748885
           ...      
242    343141.629965
243    343553.914334
244    344256.551363
245    348603.611371
246    324698.730739
Name: geometry, Length: 247, dtype: float64
In [39]:
#Ahora calculamos las distancias de cada río a cada aeropuerto
distanceMatrixKM_riv_air=rios_ukr_638.set_index('NOMBRE').geometry.apply\
(lambda g: airports_ukr_6381.set_index('airportName').geometry.distance(g)/1000).\
sort_index(axis=0).sort_index(axis=1)
distanceMatrixKM_riv_air
Out[39]:
airportName Aeroclub Swallow Aerodrom Belz Aerodrom Krupske Anan'iv Airstrip Andrushivka Artek Heliport Artsyz Air Base Askaniya-Nova Airport Bagerovo Air Base Bekhtery Airfield ... Zabroshennyy Airport Zahnitkiv Airstrip Zaporizhzhia International Airport Zavodskoe Airfield Zhalizhnia Zhovti Vody Airstrip Zhovtneve Air Base Zhovtneve Air Base 2 Zhytomyr Airport Zmiyinyy Island Helipad
NOMBRE
Danubio 407.999649 632.247250 543.874886 253.631286 510.502830 373.466037 55.227880 340.760976 517.500357 229.380486 ... 457.907645 289.525236 521.358109 346.864022 623.500891 444.531522 34.939698 667.602632 536.814542 38.087803
Desna 382.177146 470.641629 484.839850 323.927387 127.767829 729.201288 522.271359 519.087731 718.418031 500.224868 ... 123.867307 305.624653 451.002704 684.325945 433.726349 322.656147 566.699727 435.087001 134.599231 592.717682
Dnieper 373.875873 467.101601 482.226685 227.335477 121.050347 258.293189 244.256486 45.679276 245.030655 32.211690 ... 94.972041 270.494951 16.399629 214.079716 429.963058 71.195946 307.328171 425.803830 132.438773 222.743258
Dniester 18.104121 93.768252 0.377571 125.188152 193.572835 348.603611 80.577930 252.282810 459.011459 139.399831 ... 182.604690 38.641064 416.285523 311.827161 113.437530 324.377640 141.573980 159.703933 207.565289 95.681231
Goryn' 115.109010 127.965349 115.282369 355.113162 151.396486 840.888001 500.454242 659.148636 884.451658 594.369866 ... 228.396044 276.483119 672.594325 797.403732 104.438426 521.939818 511.609118 112.274612 131.369607 596.793294
Ingulets 487.601614 654.449467 633.790777 227.119223 301.360137 266.805581 275.681233 76.432126 305.117741 65.497558 ... 219.619114 287.076734 148.776213 221.820031 621.853433 10.804155 339.570064 637.663403 330.610197 258.347164
Oskol 840.819137 983.994124 978.648601 581.082689 622.472554 566.833768 708.732756 414.236759 427.135848 508.410901 ... 554.241856 644.494292 212.445766 538.905088 948.460865 309.363972 773.625516 953.430742 643.802540 703.906280
Pripyat' 327.510191 113.246762 216.387579 392.476892 165.464640 794.885748 590.173258 583.238683 776.786636 568.775951 ... 188.552802 368.865717 510.027116 750.136667 111.967651 380.765154 633.013228 68.435158 155.321077 662.085578
Prut 52.381487 210.387808 111.110932 259.800391 264.297564 724.552252 331.944284 578.475458 806.472802 487.619584 ... 281.449730 174.939219 655.195021 684.780699 212.995931 510.521901 329.738035 261.523753 274.642962 432.590770
Psel 555.033283 705.887710 695.023596 307.191492 344.846463 504.946536 468.107001 292.459425 456.427581 327.290730 ... 271.369574 361.503680 184.876707 462.682211 670.293489 75.582608 530.362448 676.244846 365.529495 493.650345
San 230.336367 155.934215 92.499855 545.589244 453.473921 1005.665102 596.438152 865.005838 1092.988247 772.960506 ... 511.603756 459.073710 931.495509 967.275520 186.955845 782.636248 575.937257 224.463494 442.031204 695.035027
Severskiy Donets 784.525232 913.468887 915.137995 549.373513 554.240391 617.557949 698.001772 439.714635 497.534770 518.366143 ... 492.501103 603.294426 239.340165 584.537666 877.179498 287.021736 762.068773 880.287196 572.805851 706.946084
Severskiy Donets 763.005930 896.641331 895.810276 522.623548 536.234459 557.992308 667.830374 395.785326 411.426947 484.798752 ... 472.177121 578.211421 192.122150 529.580385 860.637126 257.531343 732.082525 865.059205 555.908535 675.191494
Seym 554.872421 618.448404 646.907164 462.393552 300.587909 747.324582 657.838425 537.716259 673.900944 571.826959 ... 288.129552 464.903058 387.004805 706.339781 580.693991 322.632116 711.016206 572.343113 301.798904 710.167747
Siret 73.919385 264.437345 172.008606 296.072825 312.810433 745.891645 340.699683 610.179739 836.677293 514.510050 ... 331.529852 215.160818 696.840758 707.521975 261.461600 554.231345 329.254437 308.826977 321.331961 440.830406
Sluch' 101.211413 186.567308 168.609472 295.909175 87.767553 778.819171 451.055346 592.492134 816.433705 532.494169 ... 159.219551 220.983023 602.747280 734.875299 159.362126 451.863435 467.232475 159.160145 71.861145 545.212816
Sozh 491.375632 513.459599 556.617447 482.526535 252.962676 869.432884 680.639880 655.890350 838.098948 650.046337 ... 279.433757 459.565119 561.192942 825.060793 475.909857 445.398776 723.878858 460.702799 239.717183 751.110172
Teterev 175.510691 291.815210 283.423652 278.245869 25.819882 756.078724 441.077508 555.923076 762.962005 513.924179 ... 103.701726 207.570528 498.441604 711.231953 259.105341 366.919428 464.784797 277.305800 4.538553 533.189509
Tisza 135.049293 228.107539 124.968076 424.216362 388.568809 870.786768 454.719821 739.837625 966.370427 643.817459 ... 428.229876 340.692851 821.044187 834.216642 238.998931 675.632033 428.354658 287.472615 387.024765 550.975965
Yuzhnyy Bug 94.334707 222.173887 196.552821 52.377391 76.545789 340.757865 228.784841 161.174644 390.015775 99.101046 ... 94.261821 64.006196 275.670535 296.259353 195.385767 173.214730 292.543489 226.399484 92.970292 240.006476

20 rows × 247 columns

In [40]:
#La distancia de cada aeropuerto al mismo río
distanceMatrixKM_riv_air.loc['Dniester'].sort_values()
Out[40]:
airportName
Aerodrom Krupske                           0.377571
Sambir Air Base                            1.161449
Pidverbtsi Airstrip                        2.585549
Liubsha Air Base                           4.498998
Pogorelovka Airstrip                       7.607976
                                            ...    
Sievierodonetsk Airport                  685.760232
Luhansk Aviation Sports Club Airfield    712.953957
Luhansk International Airport            726.152312
Dmitrievka Airfield                      727.602941
Gostra Mogila Airfield                   731.275229
Name: Dniester, Length: 247, dtype: float64
In [41]:
#Graficamos el río y los aeropuertos
base=rios_ukr_638[rios_ukr_638.NOMBRE.str.contains('Dniester')].explore()
airports_ukr_6381.explore(m=base,color='red',marker_kwds=dict(radius=10))
Out[41]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [42]:
#Creamos dos sistemas
SYSTEM1 = rios_ukr_638.iloc[2:3]
SYSTEM1.unary_union
Out[42]:
In [43]:
SYSTEM1.plot()
Out[43]:
<Axes: >
In [44]:
SYSTEM2 = rios_ukr_638.iloc[7:10]
type(SYSTEM2.unary_union)
Out[44]:
shapely.geometry.multilinestring.MultiLineString
In [45]:
SYSTEM2.plot()
Out[45]:
<Axes: >
In [46]:
#Los unimos y creamos sus hulls
SYSTEM2_hull=gpd.GeoSeries(SYSTEM2.unary_union.convex_hull)
In [47]:
SYSTEM1_hull=gpd.GeoSeries(SYSTEM1.unary_union.convex_hull)
In [48]:
SYSTEM1_hull.plot()
Out[48]:
<Axes: >
In [49]:
SYSTEM2_hull.plot()
Out[49]:
<Axes: >
In [50]:
#Ahora calculamos su distancia a cada aeropuerto
distanceMatrixKM_sys_air=SYSTEM1.set_index('NOMBRE').geometry.apply\
(lambda g: airports_ukr_6381.set_index('airportName').geometry.distance(g)/1000).\
sort_index(axis=0).sort_index(axis=1)

distanceMatrixKM_sys_air
Out[50]:
airportName Aeroclub Swallow Aerodrom Belz Aerodrom Krupske Anan'iv Airstrip Andrushivka Artek Heliport Artsyz Air Base Askaniya-Nova Airport Bagerovo Air Base Bekhtery Airfield ... Zabroshennyy Airport Zahnitkiv Airstrip Zaporizhzhia International Airport Zavodskoe Airfield Zhalizhnia Zhovti Vody Airstrip Zhovtneve Air Base Zhovtneve Air Base 2 Zhytomyr Airport Zmiyinyy Island Helipad
NOMBRE
Prut 52.381487 210.387808 111.110932 259.800391 264.297564 724.552252 331.944284 578.475458 806.472802 487.619584 ... 281.44973 174.939219 655.195021 684.780699 212.995931 510.521901 329.738035 261.523753 274.642962 432.59077

1 rows × 247 columns

In [51]:
#el aeropuerto con mínima distancia a este sistema
mins=distanceMatrixKM_sys_air.idxmin(axis="columns")
mins
Out[51]:
NOMBRE
Prut    Mamalyha Heliport
dtype: object
In [52]:
#el aeropuerto con máximas distancias a este sistema
maxs=distanceMatrixKM_sys_air.idxmax(axis="columns")
maxs
Out[52]:
NOMBRE
Prut    Gostra Mogila Airfield
dtype: object
In [53]:
#Ahora plotearemos
base=SYSTEM1.explore()
# Los más cercanos los graficamos de rojo
airports_ukr_6381[airports_ukr_6381.airportName.isin(mins)].explore(m=base,color='red',marker_kwds=dict(radius=10))
# Los restantes los graficamos de azul
airports_ukr_6381[airports_ukr_6381.airportName.isin(maxs)].explore(m=base,color='blue',marker_kwds=dict(radius=5))
Out[53]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [54]:
#Ahora calculamos su distancia a cada aeropuerto
distanceMatrixKM_sys_air2=SYSTEM2.set_index('NOMBRE').geometry.apply\
(lambda g: airports_ukr_6381.set_index('airportName').geometry.distance(g)/1000).\
sort_index(axis=0).sort_index(axis=1)

distanceMatrixKM_sys_air2
Out[54]:
airportName Aeroclub Swallow Aerodrom Belz Aerodrom Krupske Anan'iv Airstrip Andrushivka Artek Heliport Artsyz Air Base Askaniya-Nova Airport Bagerovo Air Base Bekhtery Airfield ... Zabroshennyy Airport Zahnitkiv Airstrip Zaporizhzhia International Airport Zavodskoe Airfield Zhalizhnia Zhovti Vody Airstrip Zhovtneve Air Base Zhovtneve Air Base 2 Zhytomyr Airport Zmiyinyy Island Helipad
NOMBRE
Desna 382.177146 470.641629 484.839850 323.927387 127.767829 729.201288 522.271359 519.087731 718.418031 500.224868 ... 123.867307 305.624653 451.002704 684.325945 433.726349 322.656147 566.699727 435.087001 134.599231 592.717682
Dnieper 373.875873 467.101601 482.226685 227.335477 121.050347 258.293189 244.256486 45.679276 245.030655 32.211690 ... 94.972041 270.494951 16.399629 214.079716 429.963058 71.195946 307.328171 425.803830 132.438773 222.743258
Seym 554.872421 618.448404 646.907164 462.393552 300.587909 747.324582 657.838425 537.716259 673.900944 571.826959 ... 288.129552 464.903058 387.004805 706.339781 580.693991 322.632116 711.016206 572.343113 301.798904 710.167747

3 rows × 247 columns

In [55]:
#el aeropuerto con mínima distancia a este sistema
mins2=distanceMatrixKM_sys_air2.idxmin(axis="columns")
mins2
Out[55]:
NOMBRE
Desna      Chernihiv Shestovytsia Airport
Dnieper                Hydropark Heliport
Seym                     Konotop Air Base
dtype: object
In [56]:
#el aeropuerto con máximas distancias a este sistema
maxs2=distanceMatrixKM_sys_air2.idxmax(axis="columns")
maxs2
Out[56]:
NOMBRE
Desna      Respect Hall Helipad
Dnieper       Kosino Spa Resort
Seym          Kosino Spa Resort
dtype: object
In [57]:
#Ahora plotearemos
base=SYSTEM2.explore()
# Los más cercanos los graficamos de rojo
airports_ukr_6381[airports_ukr_6381.airportName.isin(mins2)].explore(m=base,color='red',marker_kwds=dict(radius=10))
# Los restantes los graficamos de azul
airports_ukr_6381[airports_ukr_6381.airportName.isin(maxs2)].explore(m=base,color='blue',marker_kwds=dict(radius=5))
Out[57]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [58]:
#Ejercicio 3
In [59]:
#lo convertimos en un gdf
SYSTEM1_hull=gpd.GeoSeries(SYSTEM1.unary_union.convex_hull).to_frame()
SYSTEM1_hull
Out[59]:
0
0 POLYGON ((565664.397 5336325.726, 565416.159 5...
In [60]:
#Le damos un crs y lo proyectamos
SYSTEM1_hull.rename(columns={0:'geometry'},inplace=True)
SYSTEM1_hull=SYSTEM1_hull.set_geometry('geometry')
SYSTEM1_hull.crs="EPSG:6381"
#y verificamos:
SYSTEM1_hull.crs
Out[60]:
<Projected CRS: EPSG:6381>
Name: UCS-2000 / Ukraine TM zone 7
Axis Info [cartesian]:
- X[north]: Northing (metre)
- Y[east]: Easting (metre)
Area of Use:
- name: Ukraine - west of 22°30'E.
- bounds: (22.15, 48.24, 22.5, 48.98)
Coordinate Operation:
- name: Ukraine TM zone 7
- method: Transverse Mercator
Datum: Ukraine 2000
- Ellipsoid: Krassowsky 1940
- Prime Meridian: Greenwich
In [61]:
#Graficando los dos sistemas
from matplotlib import pyplot
fig, axs = pyplot.subplots(ncols=2,sharex=False, sharey=False,figsize=(5,5))
axs[0].set_title('System 1',fontsize=5)
SYSTEM1_hull.plot(ax=axs[0])

axs[1].set_title('System 2',fontsize=5)
SYSTEM2_hull.plot(ax=axs[1])
Out[61]:
<Axes: title={'center': 'System 2'}>
In [62]:
#Hacemos lo mismo con el segundo sistema
SYSTEM2_hull=gpd.GeoSeries(SYSTEM2.unary_union.convex_hull).to_frame()
SYSTEM2_hull.rename(columns={0:'geometry'},inplace=True)
SYSTEM2_hull=SYSTEM2_hull.set_geometry('geometry')
SYSTEM2_hull.crs="EPSG:6381"
#y verificamos:
SYSTEM1_hull.crs
Out[62]:
<Projected CRS: EPSG:6381>
Name: UCS-2000 / Ukraine TM zone 7
Axis Info [cartesian]:
- X[north]: Northing (metre)
- Y[east]: Easting (metre)
Area of Use:
- name: Ukraine - west of 22°30'E.
- bounds: (22.15, 48.24, 22.5, 48.98)
Coordinate Operation:
- name: Ukraine TM zone 7
- method: Transverse Mercator
Datum: Ukraine 2000
- Ellipsoid: Krassowsky 1940
- Prime Meridian: Greenwich
In [63]:
#La distancia del primer sistema a cada aeropuerto es
distanceMatrixKM_sysHull_air=SYSTEM1_hull.geometry.apply\
(lambda g: airports_ukr_6381.set_index('airportName').geometry.distance(g)/1000).\
sort_index(axis=0).sort_index(axis=1)

distanceMatrixKM_sysHull_air
Out[63]:
airportName Aeroclub Swallow Aerodrom Belz Aerodrom Krupske Anan'iv Airstrip Andrushivka Artek Heliport Artsyz Air Base Askaniya-Nova Airport Bagerovo Air Base Bekhtery Airfield ... Zabroshennyy Airport Zahnitkiv Airstrip Zaporizhzhia International Airport Zavodskoe Airfield Zhalizhnia Zhovti Vody Airstrip Zhovtneve Air Base Zhovtneve Air Base 2 Zhytomyr Airport Zmiyinyy Island Helipad
0 48.099989 210.387808 111.110932 259.800391 264.297564 724.552252 331.944284 578.475458 806.472802 487.619584 ... 281.44973 174.939219 655.195021 684.780699 212.995931 510.521901 329.738035 261.523753 274.642962 432.59077

1 rows × 247 columns

In [64]:
#La mínima distancia es:
mins=distanceMatrixKM_sysHull_air.idxmin(axis="columns")
mins
Out[64]:
0    Chernivtsi International Airport
dtype: object
In [65]:
#La máxima distancia es:
maxs=distanceMatrixKM_sysHull_air.idxmax(axis="columns")
maxs
Out[65]:
0    Gostra Mogila Airfield
dtype: object
In [66]:
#Graficamos el hull con el aeropuerto más cercano de rojo, y los restantes de azul
base=SYSTEM1_hull.explore()
airports_ukr_6381[airports_ukr_6381.airportName.isin(mins)].explore(m=base,color='red',marker_kwds=dict(radius=10))
airports_ukr_6381[airports_ukr_6381.airportName.isin(maxs)].explore(m=base,color='blue',marker_kwds=dict(radius=5))
Out[66]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [67]:
#La distancia del segundo sistema a cada aeropuerto es
distanceMatrixKM_sysHull_air2=SYSTEM2_hull.geometry.apply\
(lambda g: airports_ukr_6381.set_index('airportName').geometry.distance(g)/1000).\
sort_index(axis=0).sort_index(axis=1)

distanceMatrixKM_sysHull_air2
Out[67]:
airportName Aeroclub Swallow Aerodrom Belz Aerodrom Krupske Anan'iv Airstrip Andrushivka Artek Heliport Artsyz Air Base Askaniya-Nova Airport Bagerovo Air Base Bekhtery Airfield ... Zabroshennyy Airport Zahnitkiv Airstrip Zaporizhzhia International Airport Zavodskoe Airfield Zhalizhnia Zhovti Vody Airstrip Zhovtneve Air Base Zhovtneve Air Base 2 Zhytomyr Airport Zmiyinyy Island Helipad
0 370.407506 467.070458 482.223953 137.920173 121.050347 256.879448 243.852782 44.89815 243.08306 32.21169 ... 77.283353 198.925744 11.16907 212.064191 429.80616 0.0 307.327947 425.80383 132.189821 222.743258

1 rows × 247 columns

In [68]:
#La mínima distancia es:
mins2=distanceMatrixKM_sysHull_air2.idxmin(axis="columns")
mins2
Out[68]:
0    Boryspil International Airport
dtype: object
In [69]:
#La máxima distancia es:
maxs2=distanceMatrixKM_sysHull_air2.idxmax(axis="columns")
maxs2
Out[69]:
0    Kosino Spa Resort
dtype: object
In [70]:
#Graficamos el hull con el aeropuerto más cercano de rojo, y los restantes de azul
base=SYSTEM2_hull.explore()
airports_ukr_6381[airports_ukr_6381.airportName.isin(mins2)].explore(m=base,color='red',marker_kwds=dict(radius=10))
airports_ukr_6381[airports_ukr_6381.airportName.isin(maxs2)].explore(m=base,color='blue',marker_kwds=dict(radius=5))
Out[70]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [71]:
#Ejercicio 4
distanceMatrixKM_riv_air
Out[71]:
airportName Aeroclub Swallow Aerodrom Belz Aerodrom Krupske Anan'iv Airstrip Andrushivka Artek Heliport Artsyz Air Base Askaniya-Nova Airport Bagerovo Air Base Bekhtery Airfield ... Zabroshennyy Airport Zahnitkiv Airstrip Zaporizhzhia International Airport Zavodskoe Airfield Zhalizhnia Zhovti Vody Airstrip Zhovtneve Air Base Zhovtneve Air Base 2 Zhytomyr Airport Zmiyinyy Island Helipad
NOMBRE
Danubio 407.999649 632.247250 543.874886 253.631286 510.502830 373.466037 55.227880 340.760976 517.500357 229.380486 ... 457.907645 289.525236 521.358109 346.864022 623.500891 444.531522 34.939698 667.602632 536.814542 38.087803
Desna 382.177146 470.641629 484.839850 323.927387 127.767829 729.201288 522.271359 519.087731 718.418031 500.224868 ... 123.867307 305.624653 451.002704 684.325945 433.726349 322.656147 566.699727 435.087001 134.599231 592.717682
Dnieper 373.875873 467.101601 482.226685 227.335477 121.050347 258.293189 244.256486 45.679276 245.030655 32.211690 ... 94.972041 270.494951 16.399629 214.079716 429.963058 71.195946 307.328171 425.803830 132.438773 222.743258
Dniester 18.104121 93.768252 0.377571 125.188152 193.572835 348.603611 80.577930 252.282810 459.011459 139.399831 ... 182.604690 38.641064 416.285523 311.827161 113.437530 324.377640 141.573980 159.703933 207.565289 95.681231
Goryn' 115.109010 127.965349 115.282369 355.113162 151.396486 840.888001 500.454242 659.148636 884.451658 594.369866 ... 228.396044 276.483119 672.594325 797.403732 104.438426 521.939818 511.609118 112.274612 131.369607 596.793294
Ingulets 487.601614 654.449467 633.790777 227.119223 301.360137 266.805581 275.681233 76.432126 305.117741 65.497558 ... 219.619114 287.076734 148.776213 221.820031 621.853433 10.804155 339.570064 637.663403 330.610197 258.347164
Oskol 840.819137 983.994124 978.648601 581.082689 622.472554 566.833768 708.732756 414.236759 427.135848 508.410901 ... 554.241856 644.494292 212.445766 538.905088 948.460865 309.363972 773.625516 953.430742 643.802540 703.906280
Pripyat' 327.510191 113.246762 216.387579 392.476892 165.464640 794.885748 590.173258 583.238683 776.786636 568.775951 ... 188.552802 368.865717 510.027116 750.136667 111.967651 380.765154 633.013228 68.435158 155.321077 662.085578
Prut 52.381487 210.387808 111.110932 259.800391 264.297564 724.552252 331.944284 578.475458 806.472802 487.619584 ... 281.449730 174.939219 655.195021 684.780699 212.995931 510.521901 329.738035 261.523753 274.642962 432.590770
Psel 555.033283 705.887710 695.023596 307.191492 344.846463 504.946536 468.107001 292.459425 456.427581 327.290730 ... 271.369574 361.503680 184.876707 462.682211 670.293489 75.582608 530.362448 676.244846 365.529495 493.650345
San 230.336367 155.934215 92.499855 545.589244 453.473921 1005.665102 596.438152 865.005838 1092.988247 772.960506 ... 511.603756 459.073710 931.495509 967.275520 186.955845 782.636248 575.937257 224.463494 442.031204 695.035027
Severskiy Donets 784.525232 913.468887 915.137995 549.373513 554.240391 617.557949 698.001772 439.714635 497.534770 518.366143 ... 492.501103 603.294426 239.340165 584.537666 877.179498 287.021736 762.068773 880.287196 572.805851 706.946084
Severskiy Donets 763.005930 896.641331 895.810276 522.623548 536.234459 557.992308 667.830374 395.785326 411.426947 484.798752 ... 472.177121 578.211421 192.122150 529.580385 860.637126 257.531343 732.082525 865.059205 555.908535 675.191494
Seym 554.872421 618.448404 646.907164 462.393552 300.587909 747.324582 657.838425 537.716259 673.900944 571.826959 ... 288.129552 464.903058 387.004805 706.339781 580.693991 322.632116 711.016206 572.343113 301.798904 710.167747
Siret 73.919385 264.437345 172.008606 296.072825 312.810433 745.891645 340.699683 610.179739 836.677293 514.510050 ... 331.529852 215.160818 696.840758 707.521975 261.461600 554.231345 329.254437 308.826977 321.331961 440.830406
Sluch' 101.211413 186.567308 168.609472 295.909175 87.767553 778.819171 451.055346 592.492134 816.433705 532.494169 ... 159.219551 220.983023 602.747280 734.875299 159.362126 451.863435 467.232475 159.160145 71.861145 545.212816
Sozh 491.375632 513.459599 556.617447 482.526535 252.962676 869.432884 680.639880 655.890350 838.098948 650.046337 ... 279.433757 459.565119 561.192942 825.060793 475.909857 445.398776 723.878858 460.702799 239.717183 751.110172
Teterev 175.510691 291.815210 283.423652 278.245869 25.819882 756.078724 441.077508 555.923076 762.962005 513.924179 ... 103.701726 207.570528 498.441604 711.231953 259.105341 366.919428 464.784797 277.305800 4.538553 533.189509
Tisza 135.049293 228.107539 124.968076 424.216362 388.568809 870.786768 454.719821 739.837625 966.370427 643.817459 ... 428.229876 340.692851 821.044187 834.216642 238.998931 675.632033 428.354658 287.472615 387.024765 550.975965
Yuzhnyy Bug 94.334707 222.173887 196.552821 52.377391 76.545789 340.757865 228.784841 161.174644 390.015775 99.101046 ... 94.261821 64.006196 275.670535 296.259353 195.385767 173.214730 292.543489 226.399484 92.970292 240.006476

20 rows × 247 columns

In [72]:
#Escogemos un río
distanceMatrixKM_riv_air.loc['Dniester'].min()
Out[72]:
0.37757058171212604
In [73]:
minMts=distanceMatrixKM_riv_air.loc['Dniester'].min()*20000

#Ahora utilizaremos un buffer
rios_ukr_638[rios_ukr_638.NOMBRE=='Dniester'].buffer(distance = minMts)
Out[73]:
1    MULTIPOLYGON (((985695.107 5188369.859, 985413...
dtype: geometry
In [74]:
# El buffer es graficado de la siguiente manera
bufferAroundAmazon=rios_ukr_638[rios_ukr_638.NOMBRE=='Dniester'].buffer(distance = minMts)
bufferAsBase=bufferAroundAmazon.explore(color='red')
rios_ukr_638[rios_ukr_638.NOMBRE=='Dniester'].explore(m=bufferAsBase,color='blue',style_kwds={'weight':0.5})
Out[74]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [75]:
#Y con los aeropuertos es así
rios_ukr_638[rios_ukr_638.NOMBRE=='Dniester'].explore(m=bufferAsBase,color='blue',style_kwds={'weight':0.5})
airports_ukr_6381.explore(m=bufferAsBase,color='black')
Out[75]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [76]:
#Identificamos los aeropuertos dentro del buffer
riversWithinBuffer=airports_ukr_6381.clip(mask=bufferAroundAmazon)
riversWithinBuffer
Out[76]:
airportName Country latitude_deg longitude_deg geometry
86 Pidverbtsi Airstrip Ukraine 48.786820 25.217443 POINT (609999.399 5414633.847)
115 Liubsha Air Base Ukraine 49.288300 24.198299 POINT (532776.600 5466741.770)
178 Aerodrom Krupske Ukraine 49.451556 24.043866 POINT (520811.639 5484430.568)
162 Sambir Air Base Ukraine 49.549999 23.334999 POINT (469082.118 5493543.696)
In [77]:
#Los graficamos
bufferAsBase=bufferAroundAmazon.explore(color='red')
rios_ukr_638[rios_ukr_638.NOMBRE=='Dniester'].explore(m=bufferAsBase,color='blue',style_kwds={'weight':0.5})
riversWithinBuffer.explore(m=bufferAsBase,color='black')
Out[77]:
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In [78]:
#La mínima distancia es
distanceMatrixKM_riv_air.min(axis=1).min()
Out[78]:
0.022843247602207368
In [79]:
#Ahora lo usamos para todos los ríos
minMinMts_5=5*distanceMatrixKM_riv_air.min(axis=1).min()*30000


allMinBuffer=rios_ukr_638.buffer(distance = minMinMts_5).explore(color='red')
rios_ukr_638.explore(m=allMinBuffer,color='blue',style_kwds={'weight':0.5})
airports_ukr_6381.explore(m=allMinBuffer,color='black')
Out[79]:
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In [80]:
#Todos los buffers po:
rios_ukr_638.buffer(distance = minMinMts_5)
Out[80]:
0     POLYGON ((422305.644 5455254.058, 422316.829 5...
1     MULTIPOLYGON (((986308.547 5200048.985, 986540...
2     POLYGON ((561530.585 5377265.597, 561619.619 5...
3     POLYGON ((617297.945 5337878.286, 617268.503 5...
4     MULTIPOLYGON (((966040.408 5067598.667, 966197...
5     POLYGON ((1154305.669 5470594.984, 1155692.428...
6     POLYGON ((1211585.985 5526485.484, 1211585.844...
7     POLYGON ((974678.806 5646911.251, 974668.855 5...
8     POLYGON ((1101617.464 5770360.708, 1101841.953...
9     POLYGON ((958233.658 5765921.015, 958176.506 5...
10    POLYGON ((973513.887 5806718.587, 973522.610 5...
11    MULTIPOLYGON (((921932.889 5747304.085, 921982...
12    POLYGON ((795722.940 5540168.553, 795686.662 5...
13    MULTIPOLYGON (((1118315.268 5283169.139, 11182...
14    POLYGON ((623469.848 5529656.700, 623263.066 5...
15    POLYGON ((684796.207 5524664.380, 685064.258 5...
16    POLYGON ((1493439.668 5582203.896, 1493572.832...
17    MULTIPOLYGON (((1688981.340 5552089.737, 16891...
18    POLYGON ((1421556.032 5640301.729, 1421554.429...
19    MULTIPOLYGON (((523865.086 5315981.912, 523263...
dtype: geometry
In [81]:
#Podemos observar que es una geoserie
riversAll_buf=rios_ukr_638.buffer(distance = minMinMts_5)
type(riversAll_buf)
Out[81]:
geopandas.geoseries.GeoSeries
In [82]:
#Lo convertimos a un geodataframe
riversAll_bufDF=riversAll_buf.to_frame()
riversAll_bufDF.rename(columns={0:'geometry'},inplace=True)
riversAll_bufDF = riversAll_bufDF.set_geometry("geometry")
riversAll_bufDF.crs
Out[82]:
<Projected CRS: EPSG:6381>
Name: UCS-2000 / Ukraine TM zone 7
Axis Info [cartesian]:
- X[north]: Northing (metre)
- Y[east]: Easting (metre)
Area of Use:
- name: Ukraine - west of 22°30'E.
- bounds: (22.15, 48.24, 22.5, 48.98)
Coordinate Operation:
- name: Ukraine TM zone 7
- method: Transverse Mercator
Datum: Ukraine 2000
- Ellipsoid: Krassowsky 1940
- Prime Meridian: Greenwich
In [83]:
#Estos son los aeropuertos que pertenecen a la zona del buffer de los ríos
allRiversWithinBuffs=airports_ukr_6381.clip(riversAll_bufDF)
allRiversWithinBuffs
Out[83]:
airportName Country latitude_deg longitude_deg geometry
190 Iskrivka Airstrip Ukraine 48.178770 33.354016 POINT (1218028.379 5412725.292)
205 Lysychansk Heliport Ukraine 48.932300 38.409700 POINT (1572798.574 5570131.814)
224 Reni Heliport Ukraine 45.425540 28.290380 POINT (870653.529 5058287.747)
194 Kiliya Airport Ukraine 45.458866 29.287591 POINT (948299.393 5069594.529)
208 Mamalyha Heliport Ukraine 48.247700 26.584730 POINT (714813.175 5361196.731)
177 Kornych Air Base Ukraine 48.528999 25.125000 POINT (604760.590 5385600.122)
195 Kolomiya Airport Ukraine 48.550999 25.042000 POINT (598502.624 5387717.900)
86 Pidverbtsi Airstrip Ukraine 48.786820 25.217443 POINT (609999.399 5414633.847)
178 Aerodrom Krupske Ukraine 49.451556 24.043866 POINT (520811.639 5484430.568)
162 Sambir Air Base Ukraine 49.549999 23.334999 POINT (469082.118 5493543.696)
34 Starokostiantyniv Air Base Ukraine 49.748299 27.273300 POINT (752087.308 5531897.487)
93 Iziaslav Ukraine 50.119643 26.868107 POINT (719666.562 5570795.921)
53 Kyiv Challenge Heliport Ukraine 50.406424 30.579473 POINT (980519.891 5630199.473)
200 Hydropark Heliport Ukraine 50.458134 30.568124 POINT (978969.838 5635831.382)
5 Dnipro International Airport Ukraine 48.357201 35.100601 POINT (1343783.385 5455169.126)
107 Dymer Airstrip Ukraine 51.007103 29.978248 POINT (929736.910 5691486.706)
187 Chоrnobil Heliport Ukraine 51.285999 30.198999 POINT (941287.027 5724348.157)
In [84]:
#Y los graficamos
base=riversAll_bufDF.plot(color='orange')
allRiversWithinBuffs.plot(ax=base, color='black', markersize=1)
Out[84]:
<Axes: >
In [85]:
#Ahora usamos folium
base=riversAll_bufDF.explore(color='orange')
allRiversWithinBuffs.explore(m=base, color='black')
Out[85]:
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